Instructions to use dima806/cat_breed_image_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dima806/cat_breed_image_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dima806/cat_breed_image_detection") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("dima806/cat_breed_image_detection") model = AutoModelForImageClassification.from_pretrained("dima806/cat_breed_image_detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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- accuracy
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- f1
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---
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Detects cat breed (from the list of 48 common breeds) with about
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See https://www.kaggle.com/code/dima806/cat-breed-image-detection-vit for more details.
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 with about 76% accuracy based on image.
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See https://www.kaggle.com/code/dima806/cat-breed-image-detection-vit for more details.
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```
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Classification report:
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precision recall f1-score support
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Abyssinian 0.9825 0.9686 0.9755 2258
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American Bobtail 0.3682 0.4756 0.4151 2258
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American Curl 0.9351 0.9128 0.9238 2258
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American Shorthair 0.2152 0.0425 0.0710 2258
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Applehead Siamese 0.9752 0.9938 0.9844 2258
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Balinese 0.9066 0.9504 0.9280 2258
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Bengal 0.7630 0.7843 0.7735 2258
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Birman 0.8670 0.9358 0.9001 2258
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Bombay 0.6385 0.8707 0.7367 2258
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British Shorthair 0.7687 0.8578 0.8108 2258
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Burmese 0.9083 0.9477 0.9276 2258
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Calico 0.6022 0.6329 0.6171 2258
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Cornish Rex 0.9942 0.9903 0.9922 2258
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Devon Rex 0.9800 1.0000 0.9899 2258
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Dilute Calico 0.5924 0.5638 0.5777 2258
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Dilute Tortoiseshell 0.5785 0.6807 0.6254 2258
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Domestic Long Hair 0.3902 0.3361 0.3612 2258
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Domestic Medium Hair 0.2924 0.1182 0.1684 2258
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Domestic Short Hair 0.9382 0.9743 0.9559 2258
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Egyptian Mau 0.8839 0.9136 0.8985 2258
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Exotic Shorthair 0.8656 0.8012 0.8321 2258
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Extra-Toes Cat - Hemingway Polydactyl 0.3749 0.1732 0.2369 2258
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Havana 0.9835 0.9774 0.9805 2258
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Himalayan 0.7831 0.7037 0.7413 2258
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Japanese Bobtail 0.9788 0.9823 0.9805 2258
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Maine Coon 0.4964 0.6355 0.5574 2258
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Manx 0.3339 0.0939 0.1466 2258
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Munchkin 0.9277 0.9495 0.9385 2258
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Nebelung 0.9693 0.9925 0.9807 2258
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Norwegian Forest 0.8262 0.8463 0.8361 2258
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Oriental Short Hair 0.8392 0.7626 0.7991 2258
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Persian 0.8177 0.7865 0.8018 2258
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Ragamuffin 0.9618 0.9818 0.9717 2258
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Ragdoll 0.6668 0.6169 0.6409 2258
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Russian Blue 0.8113 0.9066 0.8563 2258
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Scottish Fold 0.9736 0.8990 0.9348 2258
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Siamese 0.7565 0.7197 0.7376 2258
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Siberian 0.9481 0.9619 0.9549 2258
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Snowshoe 0.8209 0.8242 0.8225 2258
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Sphynx 0.9951 0.9894 0.9922 2258
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Tabby 0.3461 0.3472 0.3467 2258
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Tiger 0.4004 0.6001 0.4803 2258
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Tonkinese 0.9595 0.9451 0.9523 2258
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Torbie 0.5366 0.6435 0.5852 2258
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Tortoiseshell 0.6612 0.7994 0.7237 2258
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Turkish Angora 0.7278 0.8291 0.7752 2258
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Turkish Van 0.7509 0.9119 0.8236 2258
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Tuxedo 0.6356 0.8459 0.7258 2258
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accuracy 0.7599 108384
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macro avg 0.7444 0.7599 0.7456 108384
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weighted avg 0.7444 0.7599 0.7456 108384
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```
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